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http://dx.doi.org/10.3807/JOSK.2016.20.4.515

Study of Spectral Reflectance Reconstruction Based on an Algorithm for Improved Orthogonal Matching Pursuit  

Leihong, Zhang (College of Communication and Art Design, University of Shanghai for Science and Technology)
Dong, Liang (College of Communication and Art Design, University of Shanghai for Science and Technology)
Dawei, Zhang (School of optical electrical and computer engineering, University of Shanghai for Science and Technology)
Xiumin, Gao (School of optical electrical and computer engineering, University of Shanghai for Science and Technology)
Xiuhua, Ma (Shanghai Institute of Optics and Fine Mechanics, CAS)
Publication Information
Journal of the Optical Society of Korea / v.20, no.4, 2016 , pp. 515-523 More about this Journal
Abstract
Spectral reflectance is sparse in space, and while the traditional spectral-reconstruction algorithm does not make full use of this characteristic sparseness, the compressive sensing algorithm can make full use of it. In this paper, on the basis of analyzing compressive sensing based on the orthogonal matching pursuit algorithm, a new algorithm based on the Dice matching criterion is proposed. The Dice similarity coefficient is introduced, to calculate the correlation coefficient of the atoms and the residual error, and is used to select the atoms from a library. The accuracy of Spectral reconstruction based on the pseudo-inverse method, Wiener estimation method, OMP algorithm, and DOMP algorithm is compared by simulation on the MATLAB platform and experimental testing. The result is that spectral-reconstruction accuracy based on the DOMP algorithm is higher than for the other three methods. The root-mean-square error and color difference decreases with an increasing number of principal components. The reconstruction error decreases as the number of iterations increases. Spectral reconstruction based on the DOMP algorithm can improve the accuracy of color-information replication effectively, and high-accuracy color-information reproduction can be realized.
Keywords
Compressive sensing; Orthogonal matching pursuit; Dice coefficient; Principal component analysis; Spectral reconstruction;
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